Coding a sequence of pictures comprises different steps. Each picture is composed of a bidimensional array of picture elements or pixels, each of them having luminance and chrominance components. For encoding purposes, the picture is subdivided into non-overlapping blocks of pixels. A discrete cosine transform (DCT) is applied to each block of the picture. The coefficients obtained from this DCT are rounded to the closest value given by a fixed quantization law and then quantized, depending on the spatial frequency within the block that they represent. The quantized data thus obtained are then coded. During a decoding step, the coded data are successively decoded, treated by inverse quantization and inverse discrete cosine transform, and finally filtered before being displayed.
Quantization is, in data transmission, one of the steps for data compression and is a treatment which involves losses. The quantization errors introduced by quantization of the DCT coefficients in the coding have as a main result the occurrence of ringing artifacts. This ringing noise is the Gibb's phenomenon caused by truncation of the high-frequency coefficients through quantization during encoding. Therefore, ringing artifacts occur near high-frequency areas which are located in low activity regions and may appear as “false edges” in the picture.
A possible method of removing these ringing artifacts is proposed by Park et al. in IEEE Transactions on CSVT, vol. 9, no. 1, February 1999, pp 161–171. The disclosed method comprises, for a given picture, a first step of edge detection followed by a low-pass filtering. The edge detection step makes use of a quantized factor QP taken from the encoding stage. Furthermore, the proposed filtering step involves low-pass filtering of the luminance components by means of the derivation of weighted means of a defined set of luminance values. Thus the method proposed by the prior art involves the use of encoding parameters, which might not always be available at the edge detection stage, while the low-pass filtering may introduce blurring effects in areas of the picture where extreme values of luminance can be found.